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@@ -199,14 +199,16 @@ fairseq-interactive ${PREPROCESSED_DATA_DIR} --path ${MODEL_SAVE_DIR}/checkpoint
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```
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2. 读入模型文件
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第一个参数为checkpoints所在目录,`checkpoint_file`为需要读入的checkpoint的文件名,`data_name_or_path`为字典文件所在的目录。
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我们将模型生成的checkpoint文件拷贝到`./checkpoints`目录下,将预处理阶段生成的两份字典文件(`dict.up.txt`和`dict.down.txt`)拷贝到`./checkpoints/dict`目录下。按如下代码即可读入文件:
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```
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model = LSTMModel.from_pretrained('./checkpoints',\
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checkpoint_file='checkpoint_best.pt',\
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data_name_or_path="DICT_PATH")
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data_name_or_path="./dict")
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```
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第一个参数为checkpoint文件所在目录,`checkpoint_file`为需要读入的checkpoint的文件名,`data_name_or_path`为字典文件所在的目录。需要注意的是,字典文件目录将以第一个参数为根目录,若路径有误会出现报错信息:`AttributeError: 'NoneType' object has no attribute 'split'`。
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3. 推理
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此处需要注意输入的文字之间需用空格隔开。
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@@ -233,7 +235,7 @@ fairseq-interactive ${PREPROCESSED_DATA_DIR} --path ${MODEL_SAVE_DIR}/checkpoint
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model = LSTMModel.from_pretrained('./checkpoints',\
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checkpoint_file='checkpoint_best.pt',\
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data_name_or_path="DICT_PATH") # 读入模型
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data_name_or_path="./dict") # 读入模型
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app = Flask(__name__)
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